class_docstr: Base class = common interface for retrieving the most similar terms for a given term.
  
  See Also
  --------
  :class:`~gensim.similarities.termsim.SparseTermSimilarityMatrix`
      A sparse term similarity matrix built using a term similarity index.
docstr: Get most similar terms for a given term.
  
  Return the most similar terms for a given term along with their similarities.
  
  Parameters
  ----------
  term : str
      The term for which we are retrieving `topn` most similar terms.
  topn : int, optional
      The maximum number of most similar terms to `term` that will be retrieved.
  
  Returns
  -------
  iterable of (str, float)
      Most similar terms along with their similarities to `term`. Only terms distinct from
      `term` must be returned.
docstr_tok: ["Get","most","similar","terms","for","a","given","term",".","Return","the","most","similar","terms","for","a","given","term","along","with","their","similarities",".","Parameters","--","--","--","--","--","term",":","str","The","term","for","which","we","are","retrieving","`","topn","`","most","similar","terms",".","topn",":","int",",","optional","The","maximum","number","of","most","similar","terms","to","`","term","`","that","will","be","retrieved",".","Returns","--","--","--","-","iterable","of","(","str",",","float",")","Most","similar","terms","along","with","their","similarities","to","`","term","`",".","Only","terms","distinct","from","`","term","`","must","be","returned","."]
code: def most_similar(self, term, topn=10):
      """Get most similar terms for a given term.
  
      Return the most similar terms for a given term along with their similarities.
  
      Parameters
      ----------
      term : str
          The term for which we are retrieving `topn` most similar terms.
      topn : int, optional
          The maximum number of most similar terms to `term` that will be retrieved.
  
      Returns
      -------
      iterable of (str, float)
          Most similar terms along with their similarities to `term`. Only terms distinct from
          `term` must be returned.
  
      """
      raise NotImplementedError
  
imports: from array import array
  from itertools import chain
  import logging
  from math import sqrt
  import numpy
  from scipy import sparse
  from gensim.matutils import corpus2csc
  from gensim.utils import SaveLoad, is_corpus
label_desc: Use image node_id 1 for calling the TermSimilarityIndex obj's underlying member method code with example usage: obj.most_similar(term, topn) without return types